internal/ceres/linear_solver.cc

// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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// modification, are permitted provided that the following conditions are met:
//
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//   this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
//   this list of conditions and the following disclaimer in the documentation
//   and/or other materials provided with the distribution.
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//   used to endorse or promote products derived from this software without
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//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// Author: sameeragarwal@google.com (Sameer Agarwal)

#include "ceres/linear_solver.h"

#include "ceres/cgnr_solver.h"
#include "ceres/dense_normal_cholesky_solver.h"
#include "ceres/dense_qr_solver.h"
#include "ceres/iterative_schur_complement_solver.h"
#include "ceres/schur_complement_solver.h"
#include "ceres/dynamic_sparse_normal_cholesky_solver.h"
#include "ceres/sparse_normal_cholesky_solver.h"
#include "ceres/types.h"
#include "glog/logging.h"

namespace ceres {
namespace internal {

LinearSolver::~LinearSolver() {
}

LinearSolverType LinearSolver::LinearSolverForZeroEBlocks(
    LinearSolverType linear_solver_type) {
  if (!IsSchurType(linear_solver_type)) {
    return linear_solver_type;
  }

  if (linear_solver_type == SPARSE_SCHUR) {
    return SPARSE_NORMAL_CHOLESKY;
  }

  if (linear_solver_type == DENSE_SCHUR) {
    // TODO(sameeragarwal): This is probably not a great choice.
    // Ideally, we should have a DENSE_NORMAL_CHOLESKY, that can take
    // a BlockSparseMatrix as input.
    return DENSE_QR;
  }

  if (linear_solver_type == ITERATIVE_SCHUR) {
    return CGNR;
  }

  return linear_solver_type;
}

LinearSolver* LinearSolver::Create(const LinearSolver::Options& options) {
  switch (options.type) {
    case CGNR:
      return new CgnrSolver(options);

    case SPARSE_NORMAL_CHOLESKY:
#if defined(CERES_NO_SUITESPARSE) &&              \
    defined(CERES_NO_CXSPARSE) &&                 \
   !defined(CERES_USE_EIGEN_SPARSE)
      return NULL;
#else
      if (options.dynamic_sparsity) {
        return new DynamicSparseNormalCholeskySolver(options);
      }

      return new SparseNormalCholeskySolver(options);
#endif

    case SPARSE_SCHUR:
#if defined(CERES_NO_SUITESPARSE) &&                 \
    defined(CERES_NO_CXSPARSE) &&                    \
   !defined(CERES_USE_EIGEN_SPARSE)
      return NULL;
#else
      return new SparseSchurComplementSolver(options);
#endif

    case DENSE_SCHUR:
      return new DenseSchurComplementSolver(options);

    case ITERATIVE_SCHUR:
      if (options.use_explicit_schur_complement) {
        return new SparseSchurComplementSolver(options);
      } else {
        return new IterativeSchurComplementSolver(options);
      }

    case DENSE_QR:
      return new DenseQRSolver(options);

    case DENSE_NORMAL_CHOLESKY:
      return new DenseNormalCholeskySolver(options);

    default:
      LOG(FATAL) << "Unknown linear solver type :"
                 << options.type;
      return NULL;  // MSVC doesn't understand that LOG(FATAL) never returns.
  }
}

}  // namespace internal
}  // namespace ceres